Red Hat Enterprise Performance Tuning (RH442)

In this course, you will learn about system architecture with an emphasis on understanding the implications on system performance, methods for testing the effects of performance adjustments, open source benchmarking utilities, methods for analyzing system and networking performance, and tuning configurations for specific application loads.

This course can help you prepare for the Red Hat Certificate of Expertise in Performance Tuning exam (EX442). This version of the course does not include the exam.

 

    Nov 30 2020

    November 30 - December 4, 2020 | 11:00 AM - 5:00 PM (EST) | Virtual Classroom Live

    Date: 11/30/2020 - 12/04/2020 (Monday - Friday) | 11:00 AM - 5:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Red Hat Enterprise Performance Tuning (RH442)

    November 30 - December 4, 2020 | 11:00 AM - 5:00 PM (EST) | Virtual Classroom Live


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1. Introduction to performance tuning

  • Understand the basic principles of performance tuning and analysis

2. Collecting, graphing, and interpreting data

  • Gain proficiency in using basic analysis tools and in evaluating data

3. General tuning

  • Learn basic tuning theory and mechanisms used to tune the system

4. Hardware profiling

  • Understand and analyze hardware

5. Software profiling

  • Analyze CPU and memory performance of applications

6. Mail server tuning

  • Learn about basic storage tuning using an email server as an example

7. Large memory workload tuning

  • Understand memory management and tuning

8. HPC workload tuning

  • Understand tuning for CPU-bound applications

9. File server tuning

  • Understand storage and network tuning in the context of a file server application

10. Database server tuning

  • Tune memory and network performance using a database application as an example

11. Power usage tuning

  • Tune systems with power consumption in mind

12. Virtualization tuning

  • Tune host and guest for efficient virtualization

Note: Course outline is subject to change with technology advances and as the nature of the underlying job evolves

  • Tuning for use-case scenarios (for example, HPC, large memory, database, and file server)
  • Tuning for power consumption
  • Tuning virtual machines (host and guest)
  • Tuning memory and caches
  • Tuning CPU and memory utilization using cgroups
  • Gathering performance metrics and other data for tuning purposes

Experienced Linux system administrators responsible for maximizing resource utilization through performance tuning 

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